Video content is constructed from a sequence of still images that are presented in rapid succession to make objects depicted in the still images appear to move as the image sequence is presented. As such, if data representative of each pixel of each still image included within a particular image sequence were to be included in a video file or video stream without compression, the video file or stream could be extremely large and/or cumbersome (e.g., difficult to store, to transmit, to load, to play back, etc.). In some examples, the amount of uncompressed data needed to represent relatively high-quality video content (e.g., video content with a high resolution, a high frame rate, etc.) could be so large as to significantly limit the usability of the video content.
As a result, video encoding techniques have been developed to significantly reduce (i.e., compress) the amount of data used to represent video content transferred and stored by systems having limited resources (e.g., network bandwidth, data storage resources, etc.). Such video encoding techniques have been optimized for video content such as movies, web videos, live video calls, etc., and have been instrumental in enabling and promoting the popularity of such video content. However, as new forms of video content such as virtual and augmented reality gain in popularity, conventional video encoding techniques may fall short in offering easy and efficient options for encoding the new forms of video content. For example, there remains significant room for improvement in efficiently encoding video content that is not configured to be watched in a traditional way, but, rather, forms part of an overall dataset configured to be rendered to form a three-dimensional virtual scene to be experienced by users.